Principal Software Engineer, ML Infrastructure

• Vision: Develop and execute a strategic vision for ML Infrastructure that will unlock innovation in autonomous driving and enhance our rider experience.
• Technical acumen: Lead the design and implementation of cutting-edge infrastructure spanning all stages of an ML lifecycle from data preparation to training to evaluation, deployment, and serving.
• Partnership: Collaborate closely with cross-functional teams, including ML researchers, software engineers, data engineers, and hardware engineers, to define requirements and align on architectural decisions.
• Mentorship: Enable the engineers in the team to grow their careers by providing technical guidance and mentorship.

This role creates positive change by enabling innovations in ML and CV to make autonomous driving as seamless as possible, contributing to the development of safe, reliable, clean, and enjoyable autonomous robotaxis that reimagine transportation.

• Experience building and managing large-scale ML infrastructure that powers the development of large-scale ML models
• Excellent leadership skills with a demonstrated ability to lead high-performing engineering teams.
• Strong experience with training frameworks like PyTorch, JAX, etc., leveraging GPUs efficiently for distributed model training.
• Experience with GPU-accelerated inference using TensorRT, Ray Serve, or similar frameworks.
• Proficient in Python and/or C++.

No specific compensation, perks, or culture highlights mentioned in the job description.

Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market, aiming to provide the next generation of mobility-as-a-service in urban environments.